Model-based visual detection and tracking of rigid objects usually assumes that the appearance of those objects does not change at run-time or after datasets for those objects have been created. In practice however, many objects do not fall into this category. For example, a (turned-on) television set, shows unpredictable content on the screen, whereas the rest of the television set, e.g., the frame, etc., does not change. Another example is an object that partially consists of strongly reflective material, such as a mirror on a wall, includes an area of unpredictable content (reflection), while the frame does not change. Yet another example is the radio in the dashboard of a car, or any other device with a display, includes a dynamically changing portion (the display) and a static portion (the controls and frame). Current methods cannot model areas with a changing appearance, which consequently, creates difficulties with image based detection and tracking using images of objects with dynamically changing areas.